The delivery of a package from a consignor to a consignee typically requires sorting the package at several locations before the package reaches the final destination. A conventional delivery network typically includes a series of customer service centers that receive and deliver packages, and several intermediate hubs that provide links between the service centers. The flow of a package through this delivery network typically begins at a service center. From there, the package flows through a series of intermediate hubs before reaching the destination facility responsible for delivering the package to the destination address. Within each intermediate hub, the package is sorted according to the destination address for the package and consolidated for transport to the next intermediate hub or service center in the delivery process.
The tremendous volume of packages flowing through the intermediate hubs creates a logistical challenge. To date, sorting at the intermediate hubs is a highly manual process that relies heavily on the knowledge-base of the sorting operator. The sorting operator reads the destination address zip code from a shipping label on a package and sorts the package to the appropriate conveyor belt, bin, or chute. The appropriate sorting location for each zip code is specified in standard sorting charts. Sorting charts are well known in the art and specify the next sorting facility in the delivery chain based on the destination zip code and the service level of the package, wherein the service level of a package represents the committed delivery time for the package. The efficiency of the sorting operation depends on how quickly the sorting operator determines the appropriate sorting location for a package. To improve the efficiency, sorting operators memorize the zip codes associated with each sorting location and use the sorting charts sparingly. This highly manual process often results in sorting errors.
Due to the reliance on a knowledge-based sorting process, changing a sort plan may create signification inefficiencies and increase the opportunity for sorting mistakes. Accordingly, a proposed sorting chart change is weighed against the confusion caused by the change. As a result, many timesaving adjustments to sorting charts are discarded due to the learning curve necessary to implement the change.
In addition, sometimes it is necessary to know the path a package has taken through a delivery network. This may arise in a mistake-tracking context where a carrier desires to monitor sorting mistakes from their sorting hubs or it may be valuable if packages from a particular sorting location become contaminated. The current systems known in the art provide sorting charts at each location that specify the next sorting stop. But once a package is sorted and consolidated, the prior sorting locations for a particular package often cannot be readily determined.
Therefore an unsatisfied need exists for improved systems and methods for sorting packages within a delivery network that overcome the deficiencies in the prior art, some of which are discussed above.